Comprehensive side-by-side LLM comparison
Qwen2.5 32B Instruct leads with 4.8% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
Alibaba / Qwen
Qwen2.5-32B-Instruct is a 32-billion-parameter open-weight model from Alibaba's Qwen team, released in September 2024 as part of the Qwen2.5 series trained on 18 trillion tokens. The model is positioned as a high-capability option for developers with access to multi-GPU setups or high-VRAM hardware, offering strong performance on coding, structured reasoning, and multilingual tasks while remaining fully open under Apache 2.0. Its 128K context window and support for structured output generation made it a popular choice for document processing and agentic workflows in the open-source community.
Alibaba / Qwen
Qwen2.5-7B-Instruct is a 7-billion-parameter open-weight language model from Alibaba's Qwen team, released in September 2024 as part of the Qwen2.5 series trained on 18 trillion tokens with improved code, math, and multilingual coverage. The model delivers significantly stronger instruction-following, structured output generation, and long-context handling compared to its predecessor, supporting 128K context windows in a compact form factor. It became widely adopted as a foundation for fine-tuning, RAG pipelines, and on-device deployment due to its balance of capability and efficiency.
Launched on the same date
Qwen2.5 32B Instruct
Alibaba / Qwen
2024-09-19
Qwen2.5 7B Instruct
Alibaba / Qwen
2024-09-19
Average performance across 1 common benchmarks
Qwen2.5 32B Instruct
Qwen2.5 7B Instruct
Performance comparison across key benchmark categories
Qwen2.5 32B Instruct
Qwen2.5 7B Instruct
Available providers and their performance metrics
Qwen2.5 32B Instruct
Qwen2.5 7B Instruct
Qwen2.5 32B Instruct
Qwen2.5 7B Instruct